– Case Study –

Life Science Data Provider Finds Right Formula for Drug Search & Discovery

Training AI Platform for Predictive and Prescriptive Analytics

Challenge

A leading abstract and indexing scientific research discovery solution provides businesses, academia, and governments with a curated database of abstracts, citations, and scholarly articles across multiple disciplines. To enhance their platform to enable predictive and prescriptive analytics for drug discovery and research funding, they required annotated data. 

Enabling Predictive & Prescriptive Analytics

Life Science Data Provider Finds Right Formula for Drug Search & Discovery_Innodata

Results

SOLUTION

To begin the process of creating high-quality labeled scientific datasets, Innodata’s annotation experts set up their platform to automate the process of entity extraction to pull out relevant keywords and references from the source documents. Innodata’s experts then annotated millions of pages of scientific data, research, and articles and created structured, XML datasets that could be used to train the AI platform in predictive and prescriptive analytics. 

IMPACT

With these datasets the research discovery solution was able to provide more insight and give its users actionable intelligence. This intelligence is then used by the customer to research fund attribution, drive investments of new drug development, and avoid patent infringement. 

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(NASDAQ: INOD) Innodata is a leading data engineering company. Prestigious companies across the globe turn to Innodata for help with their biggest data challenges. By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of over 3,000 subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of digital data and ubiquitous AI.

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